OHBM2022 Combining graph theory and machine learning
Автор: Clinical Neuroanatomy Seminars
Загружено: 2022-06-28
Просмотров: 812
In this tutorial, I will demonstrate NBS-Predict, a prediction-based extension of the Network-based Statistic (Zalesky et al., 2010). NBS-Predict aims to alleviate the curse of dimensionality, lack of interpretability, and problem of generalizability. By combining the powerful features of machine learning and graph theory in a cross-validation structure, it provides a fast and convenient tool to identify neuroimaging-based biomarkers with high generalizability. Unlike generic machine learning algorithms, results derived from the toolbox are straightforwardly interpretable. NBS-Predict comes with a user-friendly graphical user interface (GUI) developed on MATLAB. Thus, it does not require any programming expertise. The toolbox provides an interactive viewer to visualize the results. The extensive user manual and usage tutorials are included in the toolbox.
Presenter: Emin Serin
Доступные форматы для скачивания:
Скачать видео mp4
-
Информация по загрузке:
